High-sensitivity cardiac troponin T is an independent predictor of inhospital mortality in emergency department patients with suspected infection: a prospective observational derivation study.

INTRODUCION

To assess the prognostic and discriminative accuracy of high-sensitivity cardiac troponin T (hs-cTnT) for prediction of inhospital mortality in emergency department (ED) patients with suspected infection.

METHODS

Prospective observational derivation study in ED patients with suspected infection. Prognostic performance of hs-cTnT (divided in four quartiles because of non-linearity) for prediction of inhospital mortality was assessed using multivariable logistic regression, correcting for predisposition, infection, response and organ failure (PIRO) score as a measure of illness severity and quality of ED treatment as quantified by the number of 'Surviving Sepsis Campaign' goals achieved. Discriminative power of hs-cTnT was assessed by receiver operator characteristics with area under the curve (AUC) analysis.

RESULTS

Hs-cTnT (median (IQR) was 57 (25-90) ng/L (n=23) in non-survivors, significantly higher than the 15 (7-28) ng/L in survivors (n=269, p<0.001). Additionally, the lowest quartile of hs-cTnT was a perfect predictor of survival because zero death occurred. Therefore, the second quartile was used as a reference category in the multivariable logistic regression analysis showing that hs-cTnT was an independent predictor of inhospital mortality: Corrected ORs were 2.2 (95% CI 0.4 to 12.1) and 5.8 (1.2 to 27.3) for the 3rd and 4th quartile compared with the 2nd hs-cTnT quartile. The AUCs of hs-TnT was 0.81 (0.74 to 0.88), similar to the AUC of 0.78 (0.68 to 0.87) of the PIRO score (p>0.05). Overall negative predictive value of hs-cTnT was 99%.

CONCLUSIONS

In ED patients with suspected infection, the routinely used biomarker hs-cTnT is an independent predictor of inhospital mortality with excellent discriminative performance. Future studies should focus on the additional value of hs-cTnT to existing risk stratification tools.